Illuminant | Realtime 2D lighting and particle system | Augmented Reality library

The reference illuminant is not the lamp that illuminates the scene. The reference illuminant is basically just the definition of white. While "pure black" is an unambiguous color (no intensity), "pure white" is not. E.g. if you look at the chromaticity diagram, there are infinitely many points near the middle you could call "white." Therefore, you have to pick one to be "white", and then you can construct the CIELAB space around that. That is, CIELAB is not a completely defined color space until you define what "white" you want to use. Different choices of "white" will give you different CIELAB coordinates. (Of course, as long as you keep track of the white point, the color can still be unambiguously converted back to XYZ.)

A very common definition of "white" is "Illuminant D65," or "statistically ideal European noontime sun," which has tristumulus coordinates (taken from the Wikipedia link) X = 95.047, Y = 100.00, Z = 108.883 for the standard 2º observer. Also according to Wikipedia, CIELAB is often implicitly understood to use Illuminant D50 as its white point. Turning the given xy coordinates back into XYZ coordinates (fixing Y = 100), I get X = 96.421, Y = 100, Z = 82.519. Pick either one, or even something else, to define your color space. If you're going to output a file or something with data in this color space, you should look into things like "embedded color profiles" for the relevant format, where you can store your choice of "white" for future programs to consume. If that's not possible, you should still document it somehow if it's going to be "user-facing."

Your current code has a nasty race condition in

I have found the problem.

I was using wrong reference white for chromatic adaptation. I was using value from wtpt, but Illuminant should be used instead as an input white.

Output white is still set to D65.

Obviously the EasyRBG RGB to XYZ conversion is flawed. It doesn't obey it's own rules. Let's do this step by step:

The input data is

R: 255 G: 0 B: 255

The first step is to map those to the zero to one range by dividing by 255. yielding this

var_R: 1 var_G: 0 var_B: 1

The next step is some manipulations, which seem to be some Gamut adjustments. But those manipulations have fix points at the extremes, meaning input values 1 or 0 don't change in this manipulation. So we are still at

var_R: 1 var_G: 0 var_B: 1

Next step is scale everything by 100

var_R: 100 var_G: 0 var_B: 100

Then there is a matrix multiplication of the vector (R,G,B) to (X,Y,Z) which is a weighted linear combination of RGB vector

X = 42.24 + 18.05 = 60.29
Y = 21.26 + 7.22 = 28.48
Y = 1.93 + 95.05 = 96.98

EasyRGB has some different result for this conversion from RGB to XYZ

X: 59.289, Y: 28.485, Z: 96.964

Those are known issues and should be fixed in a new package release soon.

Edit: 0.3.15 is up on Pypi and should be soon on Conda.

This is a question that does warrant an answer that is probably not suitable for Stack Overflow format.

ASTM E308 by itself is a 50 pages complex standard whose main body is about conversion from spectral distribution to CIE XYZ tristimulus values. It also touches conversion to CIE Lab and CIE Luv.

The spreadsheet you linked does not fully implement ASTM E308 and conveniently use the integration method for 5 nm measurement intervals without a table of tristimulus weighting factors which you technically need if the spectral data is bandpass corrected. It is fine for practical purposes but if precision is required it is important to know that ASTM E308 is very strict.

The spreadsheet is quite complex because it seems to use the Augmented SRM computation with the eigen-vectors for the hundred or so of beers.

Assuming that you want to use the ASBC method, the process should be as follows:

• Compute the beer transmission spectral distribution for given SRM and path length using the following equation:

• Convert the spectral distribution to CIE XYZ tristimulus values using the integration method for the CIE 1964 10 Degree Standard Observer and Illuminant C
• Convert the CIE XYZ tristimulus values to CIE Lab
• To go further, convert them also to sRGB
• Drink beer :)

If you don't mind reading Python, I made a Colab notebook that uses Colour and computes beer colour for a grid of SRM and path lengths:

I have updated your json input in your question, but what you want looks like this

You need to call the magic function %matplotlib notebook or %matplotlib inline after your imports in jupyter.

I would suspect that Onyx RIPCenter is using 72 as a default (which is a common default) and that it normally reads Photoshop:X/YResolution to get the DPI. Try copying the IFD0:X/YResolution to Photoshop:X/YResolution or simply setting the Photoshop:X/YResolution to 180.

In exiftool, you could use
exiftool -Photoshop:*Resolution=180 FILEorDIR

The asterisk is a wildcard which will allow both XResolution and YResolution to be set at the same time. Replace FILEorDIR with the files/directories to be processed. This command creates backup files. Add -overwrite_original to suppress the creation of backup files. Add -r to recurse into subdirectories.